Code Calibration in a Bayesian Framework

Calibration of every computational code. It uses a Bayesian framework to rule the estimation. With a new data set, the prediction will create a prevision set taking into account the new calibrated parameters. The choices between several models is also available. The methods are described in the paper Carmassi et al. (2018) .


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install.packages("CaliCo")

0.1.1 by Mathieu Carmassi, 10 months ago


Browse source code at https://github.com/cran/CaliCo


Authors: Mathieu Carmassi [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports R6, ggplot2, DiceKriging, DiceDesign, MASS, coda, parallel, gridExtra, gtools

Suggests knitr, rmarkdown

Linking to Rcpp, RcppArmadillo, Matrix


See at CRAN